Autonomous Hybrid IT Infrastructure Management
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Solution Overview
Problem
Current IT infrastructure management relies heavily on human intervention, leading to inefficiencies and increased costs due to complex deployment strategies and the need for repetitive operational tasks, making it challenging to optimize operations and ensure high uptime amidst growing business demands.
Innovation Solution
An autonomous IT infrastructure system that self-learns and manages hybrid IT environments by creating blueprints for IT infrastructure, optimizing workload placement, and using AI for monitoring and remediation, thereby reducing human intervention and improving resource efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If human operators manually manage IT infrastructure, then flexibility and adaptability are maintained, but time consumption and operational costs increase
Solution Approach 1:
The patent implements an autonomous IT infrastructure system that performs self-discovery, self-provisioning, self-monitoring, and self-optimization without human intervention. The system automatically discovers infrastructure components, provisions resources based on workload demands, monitors system health, and optimizes performance parameters, thereby eliminating repetitive manual operational tasks while maintaining adaptive management capabilities
Solution Approach 2:
The patent replaces manual mechanical operations with automated software-based systems. Specifically, it substitutes human operators with an autonomous management platform that uses AI/ML algorithms, automation scripts, and orchestration tools to perform infrastructure management tasks, thereby reducing time consumption while maintaining operational flexibility through programmable logic
2Adaptability or versatility
If complex deployment strategies are implemented to support growing business services, then service capability and adaptability improve, but operational complexity and skill requirements increase
Solution Approach 1:
The patent segments the complex IT infrastructure into modular components including compute resources, storage resources, network resources, and software applications. Each component is independently managed and provisioned through the autonomous system, which handles deployment strategies by breaking down complex service requirements into discrete resource allocations, thereby reducing operational complexity while maintaining service versatility
Solution Approach 2:
The patent implements a universal autonomous management platform that handles multiple deployment strategies (on-premise, cloud, hybrid, edge) through a single system architecture. The platform provides multi-functional capabilities including resource provisioning, workload orchestration, monitoring, and optimization across diverse infrastructure types, thereby supporting growing business services without proportionally increasing operational complexity
3Reliability
If more IT infrastructure resources are provisioned to support growing business demands, then service availability and performance improve, but infrastructure cost and resource utilization efficiency worsen
Solution Approach 1:
The patent implements dynamic resource allocation where the autonomous system continuously monitors workload demands and adjusts infrastructure resource provisioning in real-time. The system scales resources up or down based on actual usage patterns, ensuring service availability is maintained during peak demands while reducing resource consumption during low-utilization periods, thereby improving resource utilization efficiency without compromising reliability
Solution Approach 2:
The patent incorporates feedback mechanisms where the autonomous monitoring system continuously collects performance metrics, utilization data, and workload information, feeds this information to the decision-making engine, and triggers automated resource adjustment actions. This closed-loop feedback system ensures optimal resource allocation that maintains service availability while minimizing waste, thereby improving resource utilization efficiency
4Stability of the object's composition
If traditional monitoring and management approaches are used, then system stability is maintained, but proactive optimization and cost reduction opportunities are missed
Solution Approach 1:
The patent implements proactive management where the autonomous system predicts future infrastructure needs and potential issues before they impact service delivery. Using AI/ML analytics, the system forecasts workload trends, identifies optimization opportunities, and automatically provisions resources or adjusts configurations in advance, thereby maintaining system stability while improving operational efficiency through preventive rather than reactive management
Data Source
AI summary
This disclosure relates to a system and method to autonomously manage hybrid IT infrastructure. An end-to-end, integrated, and autonomous IT infrastructure is suggested to offload the repetitive business as usual (BAU) operational tasks, thereby reducing operational cost, noise, and chaos, improve resiliency, thus improving availability of the business. The autonomous IT infrastructure leads to bring in efficiency to customer business, to reduce incident reduction, optimize cost and to provide insight into any future IT infrastructure need. Herein, one or more key characteristics that make the IT infrastructure autonomous includes auto sensing an environment of the infrastructure, learning the infrastructure behavior, predicting one or more events, determining a course of action, and performing one or more actions with minimal or no human intervention.